This invention relates generally to collision avoidance systems for use in vehicles. More specifically, the invention relates to collision avoidance systems that utilize external vehicle sensors to capture data that is analyzed in order to identify potential collisions in sufficient time to facilitate avoidance of the potential collision.
People are more mobile than ever before. The number of cars and trucks (collectively “automobiles”) on the road appear to increase with each passing day. Moreover, the ongoing transportation explosion is not limited automobiles. A wide variety of different vehicles such as automobiles, motorcycles, satellites, planes, trains, boats, forklifts, mobile industrial and construction equipment, and other transportation devices (collectively “vehicles”) are used to move people and cargo from place to place. While there are many advantages to our increasingly mobile society, there are also costs associated with the ability to move. Accidents are one such cost. It would be desirable to reduce the number of accidents and/or severity of such accidents through the use of automated systems configured to identify potential hazards so that potential collisions could be avoided or mitigated. However, collision avoidance systems in the existing art suffer from several material limitations.
The diversity of human users presents many difficulties to the one-size-fits-all collision avoidance systems of the existing art. Every user of a vehicle is unique in one or more respects. People have different: braking preferences, reaction times, levels of alertness, levels of experience with the particular vehicle, vehicle use histories, risk tolerances, and a litany of other distinguishing attributes. It would be desirable for a collision avoidance system to incorporate user-based attributes in determining how the collision avoidance system reacts to a particular situation outside of the vehicle.
Similarly, attributes of the vehicle itself (e.g. vehicle-based attributes) can also present significant difficulties to a one-size-fits-all collision avoidance system. A large truck will require more time to stop than a small compact car. A large boat or train will require a substantially greater period of time than the large truck. It would be desirable for a collision avoidance system to incorporate vehicle-based attributes in determining how the collision avoidance system reacts to a particular situation while remaining a broad-based system than can be incorporated into a wide variety of objects.
User acceptance of collision avoidance systems provide a significant obstacle to the effectiveness of such systems. Warnings to users are only useful if users listen to the warnings. A system that generates an unacceptable rate of false alarms or nuisance alarms is not likely to be desired by consumers, or incorporated into the products of manufacturers. Thus, it would be desirable that concerns regarding the adverse effects of nuisance alarms and/or false alarms be effectively incorporated into the decision as to whether the system should identify a particular situation as a cause for concern. It would be desirable for a collision avoidance system to anticipate the reality that a user may already have initiated corrective action by the time that a system detects the potential threat. It would also be desirable for heuristics to be developed that effectively distinguish between a nuisance alarm and an alarm that would be valued by the user.